04, November 2020
Applications
2020
Blunden, J., Arndt, D.S. (Eds.), 2020. State of the Climate in 2019. Bull. Am. Meteorol. Soc. 101, S1–S429. https://doi.org/10.1175/2020BAMSStateoftheClimate.1
Healy, S.B., Polichtchouk, I., Horányi, A., 2020. Monthly and zonally averaged zonal wind information in the equatorial stratosphere provided by GNSS radio occultation. Q. J. R. Meteorol. Soc. qj.3870. https://doi.org/10.1002/qj.3870
Lang, T., Buehler, S.A., Burgdorf, M., Hans, I., John, V.O., 2020. A new climate data record of upper-tropospheric humidity from microwave observations. Sci. Data 7, 218. https://doi.org/10.1038/s41597-020-0560-1
Safieddine, S., Parracho, A.C., George, M., Aires, F., Pellet, V., Clarisse, L., Whitburn, S., Lezeaux, O., Thépaut, J.-N., Hersbach, H., Radnoti, G., Goettsche, F., Martin, M., Doutriaux-Boucher, M., Coppens, D., August, T., Zhou, D.K., Clerbaux, C., 2020. Artificial Neural Networks to Retrieve Land and Sea Skin Temperature from IASI. Remote Sens. 12, 2777. https://doi.org/10.3390/rs12172777
Steiner, A.K., Ladstädter, F., Randel, W.J., Maycock, A.C., Fu, Q., Claud, C., Gleisner, H., Haimberger, L., Ho, S.-P., Keckhut, P., Leblanc, T., Mears, C., Polvani, L.M., Santer, B.D., Schmidt, T., Sofieva, V., Wing, R., Zou, C.-Z., 2020. Observed Temperature Changes in the Troposphere and Stratosphere from 1979 to 2018. J. Clim. 33, 8165–8194. https://doi.org/10.1175/JCLI-D-19-0998.1
Tian, X., Zou, X., 2020. Comparison of Advanced Technology Microwave Sounder Biases Estimated Using Radio Occultation and Hurricane Florence (2018) Captured by NOAA-20 and S-NPP. Adv. Atmospheric Sci. 37, 269–277. https://doi.org/10.1007/s00376-019-9119-5
Trindade, A., Portabella, M., Stoffelen, A., Lin, W., Verhoef, A., 2020. ERAstar: A High-Resolution Ocean Forcing Product. IEEE Trans. Geosci. Remote Sens. 58, 1337–1347. https://doi.org/10.1109/TGRS.2019.2946019
Waliser, D., Gleckler, P.J., Ferraro, R., Taylor, K.E., Ames, S., Biard, J., Bosilovich, M.G., Brown, O., Chepfer, H., Cinquini, L., Durack, P.J., Eyring, V., Mathieu, P.-P., Lee, T., Pinnock, S., Potter, G.L., Rixen, M., Saunders, R., Schulz, J., Thépaut, J.-N., Tuma, M., 2020. Observations for Model Intercomparison Project (Obs4MIPs): status for CMIP6. Geosci. Model Dev. 13, 2945–2958. https://doi.org/10.5194/gmd-13-2945-2020
2019
Belmonte Rivas, M., Stoffelen, A., 2019. Characterizing ERA-Interim and ERA5 surface wind biases using ASCAT. Ocean Sci. 15, 831–852. https://doi.org/10.5194/os-15-831-2019
Blunden, J., Arndt, D.S., 2019. State of the Climate in 2018. Bull. Am. Meteorol. Soc. 100, Si-S306. https://doi.org/10.1175/2019BAMSStateoftheClimate.1
Docquier, D., Grist, J.P., Roberts, M.J., Roberts, C.D., Semmler, T., Ponsoni, L., Massonnet, F., Sidorenko, D., Sein, D.V., Iovino, D., Bellucci, A., Fichefet, T., 2019. Impact of model resolution on Arctic sea ice and North Atlantic Ocean heat transport. Clim. Dyn. 53, 4989–5017. https://doi.org/10.1007/s00382-019-04840-y
Gignac, C., Bernier, M., Chokmani, K., 2019. IcePAC – a probabilistic tool to study sea ice spatio-temporal dynamics: application to the Hudson Bay area. The Cryosphere 13, 451–468. https://doi.org/10.5194/tc-13-451-2019
Magarreiro, C., Gouveia, C., Barroso, C., Trigo, I., 2019. Modelling of Wine Production Using Land Surface Temperature and FAPAR—The Case of the Douro Wine Region. Remote Sens. 11, 604. https://doi.org/10.3390/rs11060604
Stöckli, R., Bojanowski, J.S., John, V.O., Duguay-Tetzlaff, A., Bourgeois, Q., Schulz, J., Hollmann, R., 2019. Cloud Detection with Historical Geostationary Satellite Sensors for Climate Applications. Remote Sens. 11, 1052. https://doi.org/10.3390/rs11091052
Su, C.-H., Eizenberg, N., Steinle, P., Jakob, D., Fox-Hughes, P., White, C.J., Rennie, S., Franklin, C., Dharssi, I., Zhu, H., 2019. BARRA v1.0: the Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia. Geosci. Model Dev. 12, 2049–2068. https://doi.org/10.5194/gmd-12-2049-2019
Sun, B., Reale, T., Schroeder, S., Pettey, M., Smith, R., 2019. On the Accuracy of Vaisala RS41 versus RS92 Upper-Air Temperature Observations. J. Atmospheric Ocean. Technol. 36, 635–653. https://doi.org/10.1175/JTECH-D-18-0081.1
von Schuckmann, et al., 2019. Copernicus Marine Service Ocean State Report, Issue 3. J. Oper. Oceanogr. 12, S1–S123. https://doi.org/10.1080/1755876X.2019.1633075
Zhran, M., Mousa, A., Rabah, M., Zeidan, Z., 2019. Utility of GNSS Radio Occultation technique for tropopause height investigation over Egypt. NRIAG J. Astron. Geophys. 8, 45–54. https://doi.org/10.1080/20909977.2019.1617559
2018
Buffat, R., Grassi, S., Raubal, M., 2018. A scalable method for estimating rooftop solar irradiation potential over large regions. Appl. Energy 216, 389–401. https://doi.org/10.1016/j.apenergy.2018.02.008
Buizza, R., et al., 2018. The EU-FP7 ERA-CLIM2 Project Contribution to Advancing Science and Production of Earth System Climate Reanalyses. Bull. Am. Meteorol. Soc. 99, 1003–1014. https://doi.org/10.1175/BAMS-D-17-0199.1
Hartfield, G., Blunden, J., Arndt, D.S., 2018. State of the Climate in 2017. Bull. Am. Meteorol. Soc. 99, Si-S310. https://doi.org/10.1175/2018BAMSStateoftheClimate.1
Massonnet, F., Vancoppenolle, M., Goosse, H., Docquier, D., Fichefet, T., Blanchard-Wrigglesworth, E., 2018. Arctic sea-ice change tied to its mean state through thermodynamic processes. Nat. Clim. Change 8, 599–603. https://doi.org/10.1038/s41558-018-0204-z
Seethala, C., Meirink, J.F., Horváth, Á., Bennartz, R., Roebeling, R., 2018. Evaluating the diurnal cycle of South Atlantic stratocumulus clouds as observed by MSG SEVIRI. Atmospheric Chem. Phys. 18, 13283–13304. https://doi.org/10.5194/acp-18-13283-2018
Urraca, R., Antonanzas, J., Sanz-Garcia, A., Martinez-de-Pison, F.J., 2019. Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) Method. Sensors 19, 2483. https://doi.org/10.3390/s19112483
Maranan, M., Fink, A.H., Knippertz, P., Amekudzi, L.K., Atiah, W.A., Stengel, M., 2020. A Process-Based Validation of GPM IMERG and Its Sources Using a Mesoscale Rain Gauge Network in the West African Forest Zone. J. Hydrometeorol. 21, 729–749. https://doi.org/10.1175/JHM-D-19-0257.1
Zampieri, L., Goessling, H.F., Jung, T., 2018. Bright Prospects for Arctic Sea Ice Prediction on Subseasonal Time Scales. Geophys. Res. Lett. 45, 9731–9738. https://doi.org/10.1029/2018GL079394
2017
Blunden, J., Arndt, D.S., 2017. State of the Climate in 2016. Bull. Am. Meteorol. Soc. 98, Si-S280. https://doi.org/10.1175/2017BAMSStateoftheClimate.1
Khaykin, S.M., Funatsu, B.M., Hauchecorne, A., Godin-Beekmann, S., Claud, C., Keckhut, P., Pazmino, A., Gleisner, H., Nielsen, J.K., Syndergaard, S., Lauritsen, K.B., 2017. Postmillennium changes in stratospheric temperature consistently resolved by GPS radio occultation and AMSU observations: Temperature Change from GPS-RO and AMSU. Geophys. Res. Lett. 44, 7510–7518. https://doi.org/10.1002/2017GL074353
Landy, J.C., Ehn, J.K., Babb, D.G., Thériault, N., Barber, D.G., 2017a. Sea ice thickness in the Eastern Canadian Arctic: Hudson Bay Complex & Baffin Bay. Remote Sens. Environ. 200, 281–294. https://doi.org/10.1016/j.rse.2017.08.019
Loew, A., Bell, W., Brocca, L., Bulgin, C.E., Burdanowitz, J., Calbet, X., Donner, R.V., Ghent, D., Gruber, A., Kaminski, T., Kinzel, J., Klepp, C., Lambert, J.-C., Schaepman-Strub, G., Schröder, M., Verhoelst, T., 2017. Validation practices for satellite-based Earth observation data across communities: EO VALIDATION. Rev. Geophys. 55, 779–817. https://doi.org/10.1002/2017RG000562
Marseille, G.-J., Stoffelen, A., 2017. Toward Scatterometer Winds Assimilation in the Mesoscale HARMONIE Model. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 10, 2383–2393. https://doi.org/10.1109/JSTARS.2016.2640339
Stoffelen, A., Aaboe, S., Calvet, J.-C., Cotton, J., De Chiara, G., Saldana, J.F., Mouche, A.A., Portabella, M., Scipal, K., Wagner, W., 2017. Scientific Developments and the EPS-SG Scatterometer. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 10, 2086–2097. https://doi.org/10.1109/JSTARS.2017.2696424
2016
Blunden, J., Arndt, D.S., 2016. State of the Climate in 2015. Bull. Am. Meteorol. Soc. 97, Si-S275. https://doi.org/10.1175/2016BAMSStateoftheClimate.1
Chung, E.-S., Soden, B.J., Huang, X., Shi, L., John, V.O., 2016. An assessment of the consistency between satellite measurements of upper tropospheric water vapor: Upper Tropospheric Water Vapor. J. Geophys. Res. Atmospheres 121, 2874–2887. https://doi.org/10.1002/2015JD024496
Otto, J., Brown, C., Buontempo, C., Doblas-Reyes, F., Jacob, D., Juckes, M., Keup-Thiel, E., Kurnik, B., Schulz, J., Taylor, A., Verhoelst, T., Walton, P., 2016. Uncertainty: Lessons Learned for Climate Services. Bull. Am. Meteorol. Soc. 97, ES265–ES269. https://doi.org/10.1175/BAMS-D-16-0173.1
Yang, W., John, V., Zhao, X., Lu, H., Knapp, K., 2016. Satellite Climate Data Records: Development, Applications, and Societal Benefits. Remote Sens. 8, 331. https://doi.org/10.3390/rs8040331
2015
Blunden, J., Arndt, D.S., 2015. State of the Climate in 2014. Bull. Am. Meteorol. Soc. 96, ES1–ES32. https://doi.org/10.1175/2015BAMSStateoftheClimate.1
2014
Amillo, A., Huld, T., Müller, R., 2014. A New Database of Global and Direct Solar Radiation Using the Eastern Meteosat Satellite, Models and Validation. Remote Sens. 6, 8165–8189. https://doi.org/10.3390/rs6098165
2013
Greuell, W., Meirink, J.F., Wang, P., 2013. Retrieval and validation of global, direct, and diffuse irradiance derived from SEVIRI satellite observations: Surface solar irradiance from satellite. J. Geophys. Res. Atmospheres 118, 2340–2361. https://doi.org/10.1002/jgrd.50194
2012
Roebeling, R.A., Wolters, E.L.A., Meirink, J.F., Leijnse, H., 2012. Triple Collocation of Summer Precipitation Retrievals from SEVIRI over Europe with Gridded Rain Gauge and Weather Radar Data. J. Hydrometeorol. 13, 1552–1566. https://doi.org/10.1175/JHM-D-11-089.1
2011
Mieruch, S., Noël, S., Reuter, M., Bovensmann, H., Burrows, J.P., Schröder, M., Schulz, J., 2011. A New Method for the Comparison of Trend Data with an Application to Water Vapor. J. Clim. 24, 3124–3141. https://doi.org/10.1175/2011JCLI3669.1
Prior 2011
Rinne, J., Aurela, M., Manninen, T., 2009. A Simple Method to Determine the Timing of Snow Melt by Remote Sensing with Application to the CO2 Balances of Northern Mire and Heath Ecosystems. Remote Sens. 1, 1097–1107. https://doi.org/10.3390/rs1041097
Quality Evaluation
2020
Bouillon, M., Safieddine, S., Hadji-Lazaro, J., Whitburn, S., Clarisse, L., Doutriaux-Boucher, M., Coppens, D., August, T., Jacquette, E., Clerbaux, C., 2020. Ten-Year Assessment of IASI Radiance and Temperature. Remote Sens. 12, 2393. https://doi.org/10.3390/rs12152393
Gleisner, H., Lauritsen, K.B., Nielsen, J.K., Syndergaard, S., 2020. Evaluation of the 15-year ROM SAF monthly mean GPS radio occultation climate data record. Atmospheric Meas. Tech. 13, 3081–3098. https://doi.org/10.5194/amt-13-3081-2020
Li, Y., Yuan, Y., Wang, X., 2020. Assessments of the Retrieval of Atmospheric Profiles from GNSS Radio Occultation Data in Moist Tropospheric Conditions Using Radiosonde Data. Remote Sens. 12, 2717. https://doi.org/10.3390/rs12172717
Saux Picart, S., Marsouin, A., Legendre, G., Roquet, H., Péré, S., Nano-Ascione, N., Gianelli, T., 2020. A Sea Surface Temperature data record (2004–2012) from Meteosat Second Generation satellites. Remote Sens. Environ. 240, 111687. https://doi.org/10.1016/j.rse.2020.111687
Steiner, A.K., Ladstädter, F., Ao, C.O., Gleisner, H., Ho, S.-P., Hunt, D., Schmidt, T., Foelsche, U., Kirchengast, G., Kuo, Y.-H., Lauritsen, K.B., Mannucci, A.J., Nielsen, J.K., Schreiner, W., Schwärz, M., Sokolovskiy, S., Syndergaard, S., Wickert, J., 2020. Consistency and structural uncertainty of multi-mission GPS radio occultation records. Atmospheric Meas. Tech. 13, 2547–2575. https://doi.org/10.5194/amt-13-2547-2020
Xu, X., Stoffelen, A., 2020. Improved Rain Screening for Ku-Band Wind Scatterometry. IEEE Trans. Geosci. Remote Sens. 58, 2494–2503. https://doi.org/10.1109/TGRS.2019.2951726
Xu, X., Stoffelen, A., Meirink, J.F., 2020. Comparison of Ocean Surface Rain Rates From the Global Precipitation Mission and the Meteosat Second-Generation Satellite for Wind Scatterometer Quality Control. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 13, 2173–2182. https://doi.org/10.1109/JSTARS.2020.2995178
2019
García-Haro, F.J., Camacho, F., Martínez, B., Campos-Taberner, M., Fuster, B., Sánchez-Zapero, J., Gilabert, M.A., 2019. Climate Data Records of Vegetation Variables from Geostationary SEVIRI/MSG Data: Products, Algorithms and Applications. Remote Sens. 11, 2103. https://doi.org/10.3390/rs11182103
Rüthrich, F., John, V.O., Roebeling, R.A., Quast, R., Govaerts, Y., Woolliams, E.R., Schulz, J., 2019. Climate Data Records from Meteosat First Generation Part III: Recalibration and Uncertainty Tracing of the Visible Channel on Meteosat-2–7 Using Reconstructed, Spectrally Changing Response Functions. Remote Sens. 11, 1165. https://doi.org/10.3390/rs11101165
Stöckli, R., Bojanowski, J.S., John, V.O., Duguay-Tetzlaff, A., Bourgeois, Q., Schulz, J., Hollmann, R., 2019. Cloud Detection with Historical Geostationary Satellite Sensors for Climate Applications. Remote Sens. 11, 1052. https://doi.org/10.3390/rs11091052
Tabata, T., John, V.O., Roebeling, R.A., Hewison, T., Schulz, J., 2019. Recalibration of over 35 Years of Infrared and Water Vapor Channel Radiances of the JMA Geostationary Satellites. Remote Sens. 11, 1189. https://doi.org/10.3390/rs11101189
Wang, Z., Stoffelen, A., Zhang, B., He, Y., Lin, W., Li, X., 2019. Inconsistencies in scatterometer wind products based on ASCAT and OSCAT-2 collocations. Remote Sens. Environ. 225, 207–216. https://doi.org/10.1016/j.rse.2019.03.005
Zeng, Y., Su, Z., Barmpadimos, I., Perrels, A., Poli, P., Boersma, K.F., Frey, A., Ma, X., de Bruin, K., Goosen, H., John, V.O., Roebeling, R., Schulz, J., Timmermans, W., 2019. Towards a Traceable Climate Service: Assessment of Quality and Usability of Essential Climate Variables. Remote Sens. 11, 1186. https://doi.org/10.3390/rs11101186
2018
Carrer, D., Moparthy, S., Lellouch, G., Ceamanos, X., Pinault, F., Freitas, S., Trigo, I., 2018. Land Surface Albedo Derived on a Ten Daily Basis from Meteosat Second Generation Observations: The NRT and Climate Data Record Collections from the EUMETSAT LSA SAF. Remote Sens. 10, 1262. https://doi.org/10.3390/rs10081262
Nightingale, J., Boersma, K., Muller, J.-P., Compernolle, S., Lambert, J.-C., Blessing, S., Giering, R., Gobron, N., De Smedt, I., Coheur, P., George, M., Schulz, J., Wood, A., 2018. Quality Assurance Framework Development Based on Six New ECV Data Products to Enhance User Confidence for Climate Applications. Remote Sens. 10, 1254. https://doi.org/10.3390/rs10081254
2017
Anderson, C., Figa-Saldana, J., Wilson, J.J.W., Ticconi, F., 2017. Validation and Cross-Validation Methods for ASCAT. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 10, 2232–2239. https://doi.org/10.1109/JSTARS.2016.2639784
Feltz, M.L., Borg, L., Knuteson, R.O., Tobin, D., Revercomb, H., Gambacorta, A., 2017. Assessment of NOAA NUCAPS upper air temperature profiles using COSMIC GPS radio occultation and ARM radiosondes. J. Geophys. Res. Atmospheres 122, 9130–9153. https://doi.org/10.1002/2017JD026504
Karlsson, K.-G., Anttila, K., Trentmann, J., Stengel, M., Fokke Meirink, J., Devasthale, A., Hanschmann, T., Kothe, S., Jääskeläinen, E., Sedlar, J., Benas, N., van Zadelhoff, G.-J., Schlundt, C., Stein, D., Finkensieper, S., Håkansson, N., Hollmann, R., 2017a. CLARA-A2: the second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data. Atmospheric Chem. Phys. 17, 5809–5828. https://doi.org/10.5194/acp-17-5809-2017
Riihelä, A., Key, J.R., Meirink, J.F., Kuipers Munneke, P., Palo, T., Karlsson, K.-G., 2017. An intercomparison and validation of satellite-based surface radiative energy flux estimates over the Arctic: ARCTIC RADIATIVE ENERGY FLUXES. J. Geophys. Res. Atmospheres 122, 4829–4848. https://doi.org/10.1002/2016JD026443
Thorne, P.W., Madonna, F., Schulz, J., Oakley, T., Ingleby, B., Rosoldi, M., Tramutola, E., Arola, A., Buschmann, M., Mikalsen, A.C., Davy, R., Voces, C., Kreher, K., De Maziere, M., Pappalardo, G., 2017. Making better sense of the mosaic of environmental measurement networks: a system-of-systems approach and quantitative assessment. Geosci. Instrum. Methods Data Syst. 6, 453–472. https://doi.org/10.5194/gi-6-453-2017
Urraca, Ruben, Gracia-Amillo, A.M., Koubli, E., Huld, T., Trentmann, J., Riihelä, A., Lindfors, A.V., Palmer, D., Gottschalg, R., Antonanzas-Torres, F., 2017a. Extensive validation of CM SAF surface radiation products over Europe. Remote Sens. Environ. 199, 171–186. https://doi.org/10.1016/j.rse.2017.07.013
Urraca, R., Martinez-de-Pison, E., Sanz-Garcia, A., Antonanzas, J., Antonanzas-Torres, F., 2017b. Estimation methods for global solar radiation: Case study evaluation of five different approaches in central Spain. Renew. Sustain. Energy Rev. 77, 1098–1113. https://doi.org/10.1016/j.rser.2016.11.222
Verhoef, A., Vogelzang, J., Verspeek, J., Stoffelen, A., 2017. Long-Term Scatterometer Wind Climate Data Records. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 10, 2186–2194. https://doi.org/10.1109/JSTARS.2016.2615873
Wang, Z., Stoffelen, A., Fois, F., Verhoef, A., Zhao, C., Lin, M., Chen, G., 2017. SST Dependence of Ku- and C-Band Backscatter Measurements. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 10, 2135–2146. https://doi.org/10.1109/JSTARS.2016.2600749
2016
Boylan, P., Wang, J., Cohn, S.A., Hultberg, T., August, T., 2016. Identification and intercomparison of surface-based inversions over Antarctica from IASI, ERA-Interim, and Concordiasi dropsonde data: Surface-Based Inversions Over Antarctica. J. Geophys. Res. Atmospheres 121, 9089–9104. https://doi.org/10.1002/2015JD024724
Bumke, K., König-Langlo, G., Kinzel, J., Schröder, M., 2016. HOAPS and ERA-Interim precipitation over the sea: validation against shipboard in situ measurements. Atmospheric Meas. Tech. 9, 2409–2423. https://doi.org/10.5194/amt-9-2409-2016
Göttsche, F.-M., Olesen, F.-S., Trigo, I., Bork-Unkelbach, A., Martin, M., 2016. Long Term Validation of Land Surface Temperature Retrieved from MSG/SEVIRI with Continuous in-Situ Measurements in Africa. Remote Sens. 8, 410. https://doi.org/10.3390/rs8050410
Roman, J., Knuteson, R., August, T., Hultberg, T., Ackerman, S., Revercomb, H., 2016. A global assessment of NASA AIRS v6 and EUMETSAT IASI v6 precipitable water vapor using ground-based GPS SuomiNet stations: IR PWV ASSESSMENT. J. Geophys. Res. Atmospheres 121, 8925–8948. https://doi.org/10.1002/2016JD024806
Tonboe, R.T., Eastwood, S., Lavergne, T., Sørensen, A.M., Rathmann, N., Dybkjær, G., Pedersen, L.T., Høyer, J.L., Kern, S., 2016. The EUMETSAT sea ice concentration climate data record. The Cryosphere 10, 2275–2290. https://doi.org/10.5194/tc-10-2275-2016
2015
Courcoux, N., Schröder, M., 2015b. The CM SAF ATOVS tropospheric water vapour and temperature data record: overview of methodology and evaluation. Earth Syst. Sci. Data Discuss. 8, 127–171. https://doi.org/10.5194/essdd-8-127-2015
Grossi, M., Valks, P., Loyola, D., Aberle, B., Slijkhuis, S., Wagner, T., Beirle, S., Lang, R., 2015. Total column water vapour measurements from GOME-2 MetOp-A and MetOp-B. Atmospheric Meas. Tech. 8, 1111–1133. https://doi.org/10.5194/amt-8-1111-2015
Lattanzio, A., Fell, F., Bennartz, R., Trigo, I.F., Schulz, J., 2015. Quality assessment and improvement of the EUMETSAT Meteosat Surface Albedo Climate Data Record. Atmospheric Meas. Tech. 8, 4561–4571. https://doi.org/10.5194/amt-8-4561-2015
Riihelä, A., Carlund, T., Trentmann, J., Müller, R., Lindfors, A., 2015. Validation of CM SAF Surface Solar Radiation Datasets over Finland and Sweden. Remote Sens. 7, 6663–6682. https://doi.org/10.3390/rs70606663
Wooster, M.J., Roberts, G., Freeborn, P.H., Xu, W., Govaerts, Y., Beeby, R., He, J., Lattanzio, A., Fisher, D., Mullen, R., 2015. LSA SAF Meteosat FRP products – Part 1: Algorithms, product contents, and analysis. Atmospheric Chem. Phys. 15, 13217–13239. https://doi.org/10.5194/acp-15-13217-2015
Zeng, Y., Su, Z., Calvet, J.-C., Manninen, T., Swinnen, E., Schulz, J., Roebeling, R., Poli, P., Tan, D., Riihelä, A., Tanis, C.-M., Arslan, A.-N., Obregon, A., Kaiser-Weiss, A., John, V.O., Timmermans, W., Timmermans, J., Kaspar, F., Gregow, H., Barbu, A.-L., Fairbairn, D., Gelati, E., Meurey, C., 2015. Analysis of current validation practices in Europe for space-based climate data records of essential climate variables. Int. J. Appl. Earth Obs. Geoinformation 42, 150–161. https://doi.org/10.1016/j.jag.2015.06.006
2014
Chiou, E.W., Bhartia, P.K., McPeters, R.D., Loyola, D.G., Coldewey-Egbers, M., Fioletov, V.E., Van Roozendael, M., Spurr, R., Lerot, C., Frith, S.M., 2014. Comparison of profile total ozone from SBUV (v8.6) with GOME-type and ground-based total ozone for a 16-year period (1996 to 2011). Atmospheric Meas. Tech. 7, 1681–1692. https://doi.org/10.5194/amt-7-1681-2014
Hamann, U., Walther, A., Baum, B., Bennartz, R., Bugliaro, L., Derrien, M., Francis, P.N., Heidinger, A., Joro, S., Kniffka, A., Le Gléau, H., Lockhoff, M., Lutz, H.-J., Meirink, J.F., Minnis, P., Palikonda, R., Roebeling, R., Thoss, A., Platnick, S., Watts, P., Wind, G., 2014. Remote sensing of cloud top pressure/height from SEVIRI: analysis of ten current retrieval algorithms. Atmospheric Meas. Tech. 7, 2839–2867. https://doi.org/10.5194/amt-7-2839-2014
Karlsson, K.-G., Johansson, E., 2013. On the optimal method for evaluating cloud products from passive satellite imagery using CALIPSO-CALIOP data: example investigating the CM SAF CLARA-A1 dataset. Atmospheric Meas. Tech. 6, 1271–1286. https://doi.org/10.5194/amt-6-1271-2013
Mieruch, S., Schröder, M., Noël, S., Schulz, J., 2014. Comparison of decadal global water vapor changes derived from independent satellite time series. J. Geophys. Res. Atmospheres 119, 12,489-12,499. https://doi.org/10.1002/2014JD021588
Stengel, M., Kniffka, A., Meirink, J.F., Lockhoff, M., Tan, J., Hollmann, R., 2014. CLAAS: the CM SAF cloud property data set using SEVIRI. Atmospheric Chem. Phys. 14, 4297–4311. https://doi.org/10.5194/acp-14-4297-2014
2013
Chung, E.-S., Soden, B.J., John, V.O., 2013. Intercalibrating Microwave Satellite Observations for Monitoring Long-Term Variations in Upper- and Midtropospheric Water Vapor*. J. Atmospheric Ocean. Technol. 30, 2303–2319. https://doi.org/10.1175/JTECH-D-13-00001.1
Schröder, M., Jonas, M., Lindau, R., Schulz, J., Fennig, K., 2013. The CM SAF SSM/I-based total column water vapour climate data record: methods and evaluation against re-analyses and satellite. Atmospheric Meas. Tech. 6, 765–775. https://doi.org/10.5194/amt-6-765-2013
2012
Bumke, K., Fennig, K., Strehz, A., Mecking, R., Schröder, M., 2012. HOAPS precipitation validation with ship-borne rain gauge measurements over the Baltic Sea. Tellus Dyn. Meteorol. Oceanogr. 64, 18486. https://doi.org/10.3402/tellusa.v64i0.18486
Jonkheid, B.J., Roebeling, R.A., van Meijgaard, E., 2012. A fast SEVIRI simulator for quantifying retrieval uncertainties in the CM SAF cloud physical property algorithm. Atmospheric Chem. Phys. 12, 10957–10969. https://doi.org/10.5194/acp-12-10957-2012
Loyola, D.G., Coldewey-Egbers, M., 2012. Multi-sensor data merging with stacked neural networks for the creation of satellite long-term climate data records. EURASIP J. Adv. Signal Process. 2012, 91. https://doi.org/10.1186/1687-6180-2012-91
2011
Anderson, C., Figa, J., Bonekamp, H., Wilson, J.J.W., Verspeek, J., Stoffelen, A., Portabella, M., 2011. Validation of Backscatter Measurements from the Advanced Scatterometer on MetOp-A. J. Atmospheric Ocean. Technol. 29, 77–88. https://doi.org/10.1175/JTECH-D-11-00020.1
Bugliaro, L., Zinner, T., Keil, C., Mayer, B., Hollmann, R., Reuter, M., Thomas, W., 2011. Validation of cloud property retrievals with simulated satellite radiances: a case study for SEVIRI. Atmospheric Chem. Phys. 11, 5603–5624. https://doi.org/10.5194/acp-11-5603-2011
Prior 2011
Macke, A., Kalisch, J., Hollmann, R., 2010. Validation of downward surface radiation derived from MSG data by in-situ observations over the Atlantic ocean. Meteorol. Z. 19, 155–167. https://doi.org/10.1127/0941-2948/2010/0433
Reuter, M., Thomas, W., Mieruch, S., Hollmann, R., 2010. A Method for Estimating the Sampling Error Applied to CM-SAF Monthly Mean Cloud Fractional Cover Data Retrieved From MSG SEVIRI. IEEE Trans. Geosci. Remote Sens. 48, 2469–2481. https://doi.org/10.1109/TGRS.2010.2041240
Riihelä, A., Laine, V., Manninen, T., Palo, T., Vihma, T., 2010. Validation of the Climate-SAF surface broadband albedo product: Comparisons with in situ observations over Greenland and the ice-covered Arctic Ocean. Remote Sens. Environ. 114, 2779–2790. https://doi.org/10.1016/j.rse.2010.06.014
van der A, R.J., Allaart, M.A.F., Eskes, H.J., 2010. Multi sensor reanalysis of total ozone. Atmospheric Chem. Phys. 10, 11277–11294. https://doi.org/10.5194/acp-10-11277-2010
Wilson, J.J.W., Anderson, C., Baker, M.A., Bonekamp, H., Saldaña, J.F., Dyer, R.G., Lerch, J.A., Kayal, G., Gelsthorpe, R.V., Brown, M.A., Schied, E., Schutz-Munz, S., Rostan, F., Pritchard, E.W., Wright, N.G., King, D., Onel, Ü., 2010. Radiometric Calibration of the Advanced Wind Scatterometer Radar ASCAT Carried Onboard the METOP-A Satellite. IEEE Trans. Geosci. Remote Sens. 48, 3236–3255. https://doi.org/10.1109/TGRS.2010.2045763
Behr, H.D., Hollmann, R., Müller, R.W., 2009. Surface radiation at sea validation of satellite-derived data with shipboard measurements. Meteorol. Z. 18, 61–74. https://doi.org/10.1127/0941-2948/2009/356
Ineichen, P., Barroso, C.S., Geiger, B., Hollmann, R., Marsouin, A., Mueller, R., 2009. Satellite Application Facilities irradiance products: hourly time step comparison and validation over Europe. Int. J. Remote Sens. 30, 5549–5571. https://doi.org/10.1080/01431160802680560
Loyola, D.G., Coldewey-Egbers, R.M., Dameris, M., Garny, H., Stenke, A., Van Roozendael, M., Lerot, C., Balis, D., Koukouli, M., 2009. Global long-term monitoring of the ozone layer – a prerequisite for predictions. Int. J. Remote Sens. 30, 4295–4318. https://doi.org/10.1080/01431160902825016
Reuter, M., Thomas, W., Albert, P., Lockhoff, M., Weber, R., Karlsson, K.-G., Fischer, J., 2009. The CM-SAF and FUB Cloud Detection Schemes for SEVIRI: Validation with Synoptic Data and Initial Comparison with MODIS and CALIPSO. J. Appl. Meteorol. Climatol. 48, 301–316. https://doi.org/10.1175/2008JAMC1982.1
Roebeling, R.A., Deneke, H.M., Feijt, A.J., 2008. Validation of Cloud Liquid Water Path Retrievals from SEVIRI Using One Year of CloudNET Observations. J. Appl. Meteorol. Climatol. 47, 206–222. https://doi.org/10.1175/2007JAMC1661.1
Wolters, E.L.A., Roebeling, R.A., Feijt, A.J., 2008. Evaluation of Cloud-Phase Retrieval Methods for SEVIRI on Meteosat-8 Using Ground-Based Lidar and Cloud Radar Data. J. Appl. Meteorol. Climatol. 47, 1723–1738. https://doi.org/10.1175/2007JAMC1591.1
Scientific Methods
2020
Buehler, S.A., Prange, M., Mrziglod, J., John, V.O., Burgdorf, M., Lemke, O., 2020. Opportunistic Constant Target Matching—A New Method for Satellite Intercalibration. Earth Space Sci. 7. https://doi.org/10.1029/2019EA000856
English, S., Prigent, C., Johnson, B., Yueh, S., Dinnat, E., Boutin, J., Newman, S., Anguelova, M., Meissner, T., Kazumori, M., Weng, F., Supply, A., Kilic, L., Bettenhausen, M., Stoffelen, A., Accadia, C., 2020. Reference-Quality Emission and Backscatter Modeling for the Ocean. Bull. Am. Meteorol. Soc. 101, E1593–E1601. https://doi.org/10.1175/BAMS-D-20-0085.1
Hewison, T.J., Doelling, D.R., Lukashin, C., Tobin, D., O. John, V., Joro, S., Bojkov, B., 2020. Extending the Global Space-Based Inter-Calibration System (GSICS) to Tie Satellite Radiances to an Absolute Scale. Remote Sens. 12, 1782. https://doi.org/10.3390/rs12111782
Saux Picart, S., Marsouin, A., Legendre, G., Roquet, H., Péré, S., Nano-Ascione, N., Gianelli, T., 2020. A Sea Surface Temperature data record (2004–2012) from Meteosat Second Generation satellites. Remote Sens. Environ. 240, 111687. https://doi.org/10.1016/j.rse.2020.111687
Xu, X., Stoffelen, A., Meirink, J.F., 2020. Comparison of Ocean Surface Rain Rates From the Global Precipitation Mission and the Meteosat Second-Generation Satellite for Wind Scatterometer Quality Control. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 13, 2173–2182. https://doi.org/10.1109/JSTARS.2020.2995178
2019
Bumke, K., Pilch Kedzierski, R., Schröder, M., Klepp, C., Fennig, K., 2019. Validation of HOAPS Rain Retrievals against OceanRAIN In-Situ Measurements over the Atlantic Ocean. Atmosphere 10, 15. https://doi.org/10.3390/atmos10010015
Hans, I., Burgdorf, M., Buehler, S., Prange, M., Lang, T., John, V., 2019. An Uncertainty Quantified Fundamental Climate Data Record for Microwave Humidity Sounders. Remote Sens. 11, 548. https://doi.org/10.3390/rs11050548
John, V.O., Tabata, T., Rüthrich, F., Roebeling, R., Hewison, T., Stöckli, R., Schulz, J., 2019. On the Methods for Recalibrating Geostationary Longwave Channels Using Polar Orbiting Infrared Sounders. Remote Sens. 11, 1171. https://doi.org/10.3390/rs11101171
Lavergne, T., Sørensen, A.M., Kern, S., Tonboe, R., Notz, D., Aaboe, S., Bell, L., Dybkjær, G., Eastwood, S., Gabarro, C., Heygster, G., Killie, M.A., Brandt Kreiner, M., Lavelle, J., Saldo, R., Sandven, S., Pedersen, L.T., 2019. Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records. The Cryosphere 13, 49–78. https://doi.org/10.5194/tc-13-49-2019
Quast, R., Giering, R., Govaerts, Y., Rüthrich, F., Roebeling, R., 2019. Climate Data Records from Meteosat First Generation Part II: Retrieval of the In-Flight Visible Spectral Response. Remote Sens. 11, 480. https://doi.org/10.3390/rs11050480
Stöckli, R., Bojanowski, J.S., John, V.O., Duguay-Tetzlaff, A., Bourgeois, Q., Schulz, J., Hollmann, R., 2019. Cloud Detection with Historical Geostationary Satellite Sensors for Climate Applications. Remote Sens. 11, 1052. https://doi.org/10.3390/rs11091052
2018
Govaerts, Y., Rüthrich, F., John, V., Quast, R., 2018. Climate Data Records from Meteosat First Generation Part I: Simulation of Accurate Top-of-Atmosphere Spectral Radiance over Pseudo-Invariant Calibration Sites for the Retrieval of the In-Flight Visible Spectral Response. Remote Sens. 10, 1959. https://doi.org/10.3390/rs10121959
Riihelä, A., Kallio, V., Devraj, S., Sharma, A., Lindfors, A., 2018. Validation of the SARAH-E Satellite-Based Surface Solar Radiation Estimates over India. Remote Sens. 10, 392. https://doi.org/10.3390/rs10030392
Su, Z., Timmermans, W., Zeng, Y., Schulz, J., John, V.O., Roebeling, R.A., Poli, P., Tan, D., Kaspar, F., Kaiser-Weiss, A.K., Swinnen, E., Toté, C., Gregow, H., Manninen, T., Riihelä, A., Calvet, J.-C., Ma, Y., Wen, J., 2018. An Overview of European Efforts in Generating Climate Data Records. Bull. Am. Meteorol. Soc. 99, 349–359. https://doi.org/10.1175/BAMS-D-16-0074.1
Wang, Y., Trentmann, J., Yuan, W., Wild, M., 2018. Validation of CM SAF CLARA-A2 and SARAH-E Surface Solar Radiation Datasets over China. Remote Sens. 10, 1977. https://doi.org/10.3390/rs10121977
2017
de Kloe, J., Stoffelen, A., Verhoef, A., 2017. Improved Use of Scatterometer Measurements by Using Stress-Equivalent Reference Winds. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 10, 2340–2347. https://doi.org/10.1109/JSTARS.2017.2685242
Hans, I., Burgdorf, M., John, V.O., Mittaz, J., Buehler, S.A., 2017. Noise performance of microwave humidity sounders over their lifetime. Atmospheric Meas. Tech. 10, 4927–4945. https://doi.org/10.5194/amt-10-4927-2017
Karlsson, K.-G., Håkansson, N., Mittaz, J., Hanschmann, T., Devasthale, A., 2017b. Impact of AVHRR Channel 3b Noise on Climate Data Records: Filtering Method Applied to the CM SAF CLARA-A2 Data Record. Remote Sens. 9, 568. https://doi.org/10.3390/rs9060568
Kobayashi, S., Poli, P., John, V.O., 2017. Characterisation of Special Sensor Microwave Water Vapor Profiler (SSM/T-2) radiances using radiative transfer simulations from global atmospheric reanalyses. Adv. Space Res. 59, 917–935. https://doi.org/10.1016/j.asr.2016.11.017
Koldunov, N.V., Köhl, A., Serra, N., Stammer, D., 2017. Sea ice assimilation into a coupled ocean–sea ice model using its adjoint. The Cryosphere 11, 2265–2281. https://doi.org/10.5194/tc-11-2265-2017
Rivas, M.B., Stoffelen, A., Verspeek, J., Verhoef, A., Neyt, X., Anderson, C., 2017. Cone Metrics: A New Tool for the Intercomparison of Scatterometer Records. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 10, 2195–2204. https://doi.org/10.1109/JSTARS.2017.2647842
Ticconi, F., Anderson, C., Figa-Saldana, J., Wilson, J.J.W., Bauch, H., 2017. Analysis of Radio Frequency Interference in Metop ASCAT Backscatter Measurements. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 10, 2360–2371. https://doi.org/10.1109/JSTARS.2016.2640561
Stoffelen, A., Verspeek, J.A., Vogelzang, J., Verhoef, A., 2017. The CMOD7 Geophysical Model Function for ASCAT and ERS Wind Retrievals. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 10, 2123–2134. https://doi.org/10.1109/JSTARS.2017.2681806
Tilstra, L.G., Tuinder, O.N.E., Wang, P., Stammes, P., 2017. Surface reflectivity climatologies from UV to NIR determined from Earth observations by GOME-2 and SCIAMACHY: SURFACE REFLECTIVITY CLIMATOLOGIES. J. Geophys. Res. Atmospheres 122, 4084–4111. https://doi.org/10.1002/2016JD025940
2016
Munro, R., Lang, R., Klaes, D., Poli, G., Retscher, C., Lindstrot, R., Huckle, R., Lacan, A., Grzegorski, M., Holdak, A., Kokhanovsky, A., Livschitz, J., Eisinger, M., 2016. The GOME-2 instrument on the Metop series of satellites: instrument design, calibration, and level 1 data processing – an overview. Atmospheric Meas. Tech. 9, 1279–1301. https://doi.org/10.5194/amt-9-1279-2016
Quast, R., Govaerts, Y., Rüthrich, F., Giering, R., Roebeling, R., 2016. Creating Fidelitous Climate Data Records from Meteosat First Generation Observations 1952152 Bytes. https://doi.org/10.6084/M9.FIGSHARE.3412201.V1
Tonboe, R.T., Eastwood, S., Lavergne, T., Sørensen, A.M., Rathmann, N., Dybkjær, G., Pedersen, L.T., Høyer, J.L., Kern, S., 2016. The EUMETSAT sea ice concentration climate data record. The Cryosphere 10, 2275–2290. https://doi.org/10.5194/tc-10-2275-2016
2015
Courcoux, N., Schröder, M., 2015a. The CM SAF ATOVS data record: overview of methodology and evaluation of total column water and profiles of tropospheric humidity. Earth Syst. Sci. Data 7, 397–414. https://doi.org/10.5194/essd-7-397-2015
Wooster, M.J., Roberts, G., Freeborn, P.H., Xu, W., Govaerts, Y., Beeby, R., He, J., Lattanzio, A., Fisher, D., Mullen, R., 2015. LSA SAF Meteosat FRP products – Part 1: Algorithms, product contents, and analysis. Atmospheric Chem. Phys. 15, 13217–13239. https://doi.org/10.5194/acp-15-13217-2015
2014
Borde, R., Doutriaux-Boucher, M., 2014. Extraction des vecteurs vents à partir d’images satellite. La Météorologie 8, 27. https://doi.org/10.4267/2042/54333
2013
John, V.O., Allan, R.P., Bell, W., Buehler, S.A., Kottayil, A., 2013a. Assessment of intercalibration methods for satellite microwave humidity sounders: INTERCALIBRATION METHODS FOR HUMIDITY SOUNDERS. J. Geophys. Res. Atmospheres 118, 4906–4918. https://doi.org/10.1002/jgrd.50358
John, V.O., Holl, G., Atkinson, N., Buehler, S.A., 2013b. Monitoring scan asymmetry of microwave humidity sounding channels using simultaneous all angle collocations (SAACs): SCAN BIAS OF MICROWAVE HUMIDITY SOUNDERS. J. Geophys. Res. Atmospheres 118, 1536–1545. https://doi.org/10.1002/jgrd.50154
Sanchez-Lorenzo, A., Wild, M., Trentmann, J., 2013. Validation and stability assessment of the monthly mean CM SAF surface solar radiation dataset over Europe against a homogenized surface dataset (1983–2005). Remote Sens. Environ. 134, 355–366. https://doi.org/10.1016/j.rse.2013.03.012
Schröder, M., Jonas, M., Lindau, R., Schulz, J., Fennig, K., 2013. The CM SAF SSM/I-based total column water vapour climate data record: methods and evaluation against re-analyses and satellite. Atmospheric Meas. Tech. 6, 765–775. https://doi.org/10.5194/amt-6-765-2013
2012
August, T., Klaes, D., Schlüssel, P., Hultberg, T., Crapeau, M., Arriaga, A., O’Carroll, A., Coppens, D., Munro, R., Calbet, X., 2012. IASI on Metop-A: Operational Level 2 retrievals after five years in orbit. J. Quant. Spectrosc. Radiat. Transf. 113, 1340–1371. https://doi.org/10.1016/j.jqsrt.2012.02.028
Mueller, R., Behrendt, T., Hammer, A., Kemper, A., 2012. A New Algorithm for the Satellite-Based Retrieval of Solar Surface Irradiance in Spectral Bands. Remote Sens. 4, 622–647. https://doi.org/10.3390/rs4030622
2011
Prior 2011
Andersson, A., Fennig, K., Klepp, C., Bakan, S., Graßl, H., Schulz, J., 2010. The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data – HOAPS-3. Earth Syst. Sci. Data 2, 215–234. https://doi.org/10.5194/essd-2-215-2010
Loew, A., Govaerts, Y., 2010. Towards Multidecadal Consistent Meteosat Surface Albedo Time Series. Remote Sens. 2, 957–967. https://doi.org/10.3390/rs2040957
Govaerts, Y.M., Lattanzio, A., 2007. Retrieval error estimation of surface albedo derived from geostationary large band satellite observations: Application to Meteosat-2 and Meteosat-7 data. J. Geophys. Res. 112, D05102. https://doi.org/10.1029/2006JD007313
Lattanzio, A., Govaerts, Y.M., Pinty, B., 2007. Consistency of surface anisotropy characterization with meteosat observations. Adv. Space Res. 39, 131–135. https://doi.org/10.1016/j.asr.2006.02.049
Govaerts, Y.M., Pinty, B., Taberner, M., Lattanzio, A., 2006. Spectral Conversion of Surface Albedo Derived From Meteosat First Generation Observations. IEEE Geosci. Remote Sens. Lett. 3, 23–27. https://doi.org/10.1109/LGRS.2005.854202
Roebeling, R.A., Feijt, A.J., Stammes, P., 2006. Cloud property retrievals for climate monitoring: Implications of differences between Spinning Enhanced Visible and Infrared Imager (SEVIRI) on METEOSAT-8 and Advanced Very High Resolution Radiometer (AVHRR) on NOAA-17. J. Geophys. Res. 111, D20210. https://doi.org/10.1029/2005JD006990
Pinty, B., Roveda, F., Verstraete, M.M., Gobron, N., Govaerts, Y., Martonchik, J.V., Diner, D.J., Kahn, R.A., 2000a. Surface albedo retrieval from Meteosat: 1. Theory. J. Geophys. Res. Atmospheres 105, 18099–18112. https://doi.org/10.1029/2000JD900113
Pinty, B., Roveda, F., Verstraete, M.M., Gobron, N., Govaerts, Y., Martonchik, J.V., Diner, D.J., Kahn, R.A., 2000b. Surface albedo retrieval from Meteosat: 2. Applications. J. Geophys. Res. Atmospheres 105, 18113–18134. https://doi.org/10.1029/2000JD900114
(see https://www.zotero.org/roebeling/collections/N2LZM3HI/tags/Application/collection )
(see https://www.zotero.org/roebeling/collections/N2LZM3HI/tags/Validation/collection )
(see https://www.zotero.org/roebeling/collections/N2LZM3HI/tags/Method/collection )
(Belmonte Rivas and Stoffelen, 2019; Docquier et al., 2019; Gignac et al., 2019; Landy et al., 2017b, 2017b; Marseille and Stoffelen, 2017; Massonnet et al., 2018; Stoffelen et al., 2017; Trindade et al., 2020; von Schuckmann et al., 2019; Zampieri et al., 2018)Boylan, P., Wang, J., Cohn, S. A., Hultberg, T., & August, T. (2016). Identification and intercomparison of surface‐based inversions over
Antarctica from IASI, ERA‐Interim, and Concordiasi dropsonde data. Journal of Geophysical Research: Atmospheres, 121, 9089